Stream based branch prediction index accelerator with power prediction

ABSTRACT

A computer-implemented method for predicting a taken branch that ends an instruction stream in a pipelined high frequency microprocessor includes receiving, by a processor, a first instruction within a first instruction stream, the first instruction including a first instruction address. The computer-implemented method further includes searching, by the processor, a stream-based index accelerator predictor one time for the stream; determining, by the processor, a prediction for a branch ending the branch stream; influencing, by the processor, a metadata prediction engine based on the prediction; and updating, by the processor, a stream-based index accelerator predictor with information indicative of the prediction.

BACKGROUND

The present disclosure relates to the field of microprocessor design,and more specifically, to stream based lookahead branch prediction.

Branch prediction is a performance-critical component of a pipelinedhigh frequency microprocessor. It is used to predict the direction(taken vs. not taken) and the target address of each branch instruction.This is beneficial because it allows processing to continue along abranch's predicted path rather than having to wait for the outcome ofthe branch to be determined. A penalty is incurred if a branch ispredicted incorrectly. Pipelined branch predictor takes several cyclesto make a prediction.

Traditionally, branch prediction is used to steer the flow ofinstructions down a processor pipeline along the most likely path ofcode to be executed within a program. Branch prediction uses historicalinformation to predict whether or not a given branch will be taken ornot taken, such as predicting which portion of code included in anIF-THEN-ELSE structure will be executed based on which portion of codewas executed in the past. The branch that is expected to be the firsttaken branch is then fetched and speculatively executed. If it is laterdetermined that the prediction was wrong, then the speculativelyexecuted or partially executed instructions are discarded and thepipeline starts over with the instruction proceeding the branch with thecorrect branch path, incurring a delay between the branch and the nextinstruction to be executed.

To accelerate speculative searching and efficiently power up structures,it would be advantageous to predict where a stream ends, where it goesand include information about the next stream. Rather than making abranch prediction for each search, it may also be advantageous to makethe prediction based on the start of the data stream, and make one entryper stream rather than one entry per search. It may also be advantageousto identify the most common exit point from a branch prediction streamand uses that exit point as the column prediction, which may achieveeven more efficiency for the column predictor, and thus increaseperformance as branch predictions are accelerated whenever the columnpredictor is correct.

SUMMARY

According to an embodiment of the present invention, acomputer-implemented method for predicting a branch in an instructionstream in a pipelined high frequency microprocessor is described. Themethod may include receiving, by a processor, a first instruction withina first instruction stream, the first instruction comprising a firstinstruction address; selecting, by the processor, a current row of abranch target buffer and a corresponding current row of aone-dimensional array based, at least in part, on a first count valueindicative of a first prediction accuracy; reading, by the processor,exit prediction information included in the current row of theone-dimensional array once per stream; receiving, by the processor, asecond instruction within a second instruction stream; determining, bythe processor, an a prediction accuracy for a first and a secondprediction based on the exit prediction information; incrementing afirst count value and a second count value based on the predictionaccuracy for the first and second predictions; and setting either afirst exit point of the branch prediction stream or a second exit pointof the branch prediction stream as a default target address based theprediction accuracy.

According to other embodiments, a system for predicting a branch in aninstruction stream in a pipelined high frequency microprocessor isdescribed. The system includes a processor configured to receive a firstinstruction within a first instruction stream, the first instructioncomprising a first instruction address; select a current row of a branchtarget buffer and a corresponding current row of a one-dimensional arraybased, at least in part, on a first count value indicative of a firstprediction accuracy; read exit prediction information included in thecurrent row of the one-dimensional array once per stream; receive asecond instruction within a second instruction stream; determine an aprediction accuracy for a first prediction and a second prediction basedon the exit prediction information, wherein the prediction accuracy isindicative of whether a target address of a first exit point and asecond exit point are accurate in determining a taken branch; incrementa first count value and a second count value based on the predictionaccuracy for the first and second predictions; and set either the firstexit point of the branch prediction stream or the second exit point ofthe branch prediction stream as a default target address based theprediction accuracy.

According to yet other embodiments, a computer program product forpredicting a branch in an instruction stream in a pipelined highfrequency microprocessor is described. The computer program productincludes a computer readable storage medium having program instructionsembodied on it, where the computer readable storage medium is not atransitory signal per se. The program instructions are executable by aprocessor to cause the processor to perform a method. The method mayinclude receiving, by a processor, a first instruction within a firstinstruction stream, the first instruction comprising a first instructionaddress; selecting, by the processor, a current row of a branch targetbuffer and a corresponding current row of a one-dimensional array based,at least in part, on a first count value indicative of a firstprediction accuracy; reading, by the processor, exit predictioninformation included in the current row of the one-dimensional arrayonce per stream; receiving, by the processor, a second instructionwithin a second instruction stream; determining, by the processor, an aprediction accuracy for a first and a second prediction based on theexit prediction information; incrementing a first count value and asecond count value based on the prediction accuracy for the first andsecond predictions; and setting either a first exit point of the branchprediction stream or a second exit point of the branch prediction streamas a default target address based the prediction accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The forgoing and other features, and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 is a block diagram of components of the computing deviceincluding the branch target buffer column predictor and branch targetbuffer, in accordance with an embodiment of the present invention;

FIG. 2 is a flowchart depicting a method for predicting the presence,column, and target location of a branch, on a computing device withinthe data processing environment of FIG. 1, in accordance with anembodiment of the present invention;

FIG. 3 is a block diagram depicting the structure of the branch targetbuffer and branch target buffer column predictor of FIG. 1, forpredicting the presence, and target location of a branch, in accordancewith an embodiment of the present invention;

FIG. 4 is a flowchart depicting a method for using the branch targetbuffer column predictor of FIG. 1, in accordance with an embodiment ofthe present invention;

FIG. 5 is a timing diagram illustrating the progression of successivebranch prediction searches performed using the information stored in theBTB, in accordance with an embodiment of the invention;

FIG. 6 is a timing diagram illustrating the progression of successivebranch prediction searches performed using the information stored in theBTB, in accordance with an embodiment of the invention;

FIG. 7 is a diagram illustrating a stream based column predictor (SPRED)indexed at the start of each stream;

FIG. 8 is a diagram illustrating the stream based column predictor(SPRED) of FIG. 7 having a branch not taken; and

FIG. 9 is a flowchart depicting a computer-implemented method forpredicting a branch in an instruction stream in a pipelined highfrequency microprocessor.

DETAILED DESCRIPTION

A Branch Target Buffer (BTB) is a structure that stores branch andtarget information. BTBs cache branch information and in many ways areanalogous to instruction and data caches. Branch History Tables (BHTs)and Pattern History Tables (PHTs) are additional structures that canstore additional information used for branch direction. A BHT or PHTusually uses saturating counters as a state machine to predict thedirection of branches. A BHT is indexed and tagged based on instructionaddress of the branch itself. A PHT is indexed based on the path takento get to the branch. It may or may not contain instruction addressand/or path history tags. Usually each table entry is a 2-bit saturatingcounter, but other sizes are also possible. It attempts to learn thedominant behavior of a branch, or multiple branches mapping to the sametable entry, and predicts that direction. A BTB and BHT can be combinedwith one or more tagged PHTs. The TAGE predictor combines multiple PHTs,each indexed with different history lengths. Perceptron branchpredictors are simple artificial neural networks that predict a branch'sdirection by learning correlations between bits in a global directionhistory vector and the branch outcome.

Asynchronous, lookahead branch prediction is done asynchronously fromthe main processor pipeline which begins with instruction fetching. Uponbeing restarted at a specified instruction address at the same timeframe as instruction fetching, branch prediction independently searchesthe BTB for the first branch at or after the restart address. Uponfinding a branch, the branch prediction logic reports it to theinstruction fetching logic and to the pipeline logic to allow eventualcorrelation between branch predictions and instructions being decoded.Independently from the rest of the pipeline, the branch prediction logicre-indexes itself with the predicted target address of a predicted takenbranch. For a predicted not-taken branch it continues searchingsequentially. It then looks for the next branch. This process thenrepeats. Indexing branch predictors, reading content from them, anddetermining whether or not there is a predicted taken branch and if soits target address takes multiple processor cycles in modern highfrequency designs. Conventional methods have shown that it is beneficialto speculatively re-index when it is likely the process will find ataken branch prior to actually finding one.

For a cache structure that supports N set associativity, effort must beincurred to perform tag matching against all sets to determine which ofthe N sets to select. In modern microprocessors, this effort usuallyincurs a couple of clock cycles to compute. Methods such as setprediction have been exploited to make an educated guess which of the Nsets is going to have a successful tag match, based on previous historyof the executing code.

Branch prediction, which attempts to find the location of branches in aninstruction stream being executed by a processor in an effort to avoidcostly branch wrong restart penalties, can also exploit a setassociative cache structure typically called a branch target buffer(BTB). A stream is defined as a sequence of instructions ending with ataken branch. This invention adds the Stream-based index acceleratorPREDictor (SPRED). It is indexed with the starting instruction address(IA) of a stream. Each set hit in the BTB would indicate the location ofa branch within a particular section of code, its direction andpredicted target address; set selection is utilized to determine whichof the N sets to select. Sets in branch prediction are sometimesreferred to as columns. The rate at which branch predictions can be madecan be accelerated by using a set, or column predictor, which predictswhich of the N columns in the BTB is expected to be used and then usedspeculatively.

The BTB is generally indexed using an instruction address and isincremented by a certain amount to continue searching sequentially forbranches within a region of code. Each time the processor instructionstream is restarted, such as for a wrong branch, searching starts and anew stream is started. Therefore, each predicted taken branch starts anew stream.

The branch predictor could also have knowledge as to where the takenbranch is within the current stream. For instance, each BTB search couldexamine an address space of a double quadword (2⁶ bytes) per cycle. Thepredictor could know that the taken branch that ends the current streamis k double quadwords (DQW) from the start of the stream. This takenbranch is known as the exit point from the stream.

In general, embodiments of the present invention discussed in FIGS. 1-6provide a computer system and branch target buffer column predictor(CPRED) used to predict the presence, column, and target of a branchindicated by a given row of a branch target buffer, and an approach topredict the presence and target of a branch using a branch target buffercolumn predictor. FIGS. 7-9 discuss embodiments of a branch predictormaintaining two or more exit points, where the index accelerator isindexed one time for the stream.

FIG. 1 depicts computer system 100, which is an example of a system thatincludes embodiments of the present invention. Computer system 100includes communications fabric 102, which provides communicationsbetween computer processor(s) 104, memory 106, persistent storage 108,communications unit 110, input/output (I/O) interface(s) 112, cache 116,a branch target buffer (BTB) 310, and an index accelerator 320.Communications fabric 102 can be implemented with any architecturedesigned for passing data and/or control information between processors(such as microprocessors, communications and network processors, etc.),system memory, peripheral devices, and any other hardware componentswithin a system. For example, communications fabric 102 can beimplemented with one or more buses.

Memory 106 and persistent storage 108 are computer readable storagemedia. In this embodiment, memory 106 includes random access memory(RAM). In general, memory 106 can include any suitable volatile ornon-volatile computer readable storage media. Cache 116 is a fast memorythat enhances the performance of processors 104 by holding recentlyaccessed data and data near accessed data from memory 106.

Program instructions and data used to practice embodiments of thepresent invention may be stored in persistent storage 108 for executionby one or more of the respective processors 104 via cache 116 and one ormore memories of memory 106. In an embodiment, persistent storage 108includes a magnetic hard disk drive. Alternatively, or in addition to amagnetic hard disk drive, persistent storage 108 can include a solidstate hard drive, a semiconductor storage device, read-only memory(ROM), erasable programmable read-only memory (EPROM), flash memory, orany other computer readable storage media that is capable of storingprogram instructions or digital information.

The media used by persistent storage 108 may also be removable. Forexample, a removable hard drive may be used for persistent storage 108.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage108.

Communications unit 110, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 110 includes one or more network interface cards.Communications unit 110 may provide communications through the use ofeither or both physical and wireless communications links. Programinstructions and data used to practice embodiments of the presentinvention may be downloaded to persistent storage 108 throughcommunications unit 110.

I/O interface(s) 112 allows for input and output of data with otherdevices that may be connected to each computer system. For example, I/Ointerface 112 may provide a connection to external devices 118 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 118 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention can be stored on such portablecomputer readable storage media and can be loaded onto persistentstorage 108 via I/O interface(s) 112. I/O interface(s) 112 also connectto a display 120.

Display 120 provides a mechanism to display data to a user and may be,for example, a computer monitor.

Processor(s) 104 include BTB 310, and index accelerator 320, which maybe one or more sets of hardware logic components capable of making andstoring predictions for the location of branches in an instructionstream.

FIG. 2 is a flowchart, generally depicted 200, depicting the operationalsteps used in the utilization of the branch target buffer columnpredictor, in accordance with an embodiment of the invention. It shouldbe appreciated that the process described in FIG. 2 describes theoperation of index accelerator 320 in embodiments where the predictionsdrawn from index accelerator 320 are verified by the predictions laterdrawn from BTB 310. BTB 310 may be embodied as a metadata predictionengine. In other embodiments where the predictions drawn from indexaccelerator 320 differ from the predictions drawn from BTB 310, theinformation stored in index accelerator 320 is updated using the processdescribed in greater detail with respect to FIG. 4. The structure andusage of index accelerator 320 and BTB 310 are described in greaterdetail with respect to FIGS. 3-9.

In step 205, a microprocessor such as processor(s) 104 receives a streamof instructions describing one or more operations which themicroprocessor is to perform, and identifies the address of the firstinstruction present in the instruction stream. In some embodiments, oneor more branches may be present in the instruction stream at variouslocations. In general, a branch represents a possible break in thesequential instruction stream which describes a new location within theinstruction stream where processing is to jump to. In some embodiments,two-way branching is implemented within a high level programminglanguage with a conditional jump instruction such as an if-then-elsestructure. In these embodiments, a conditional jump can either be “nottaken” and continue execution with the set of instructions which followimmediately after the conditional jump in the instruction stream, or itcan be a “taken” branch and jump to a different place in instructionstream. In general, a branch such as a two-way branch is predicted usinginformation stored in BTB 310 to be either a “taken” branch or a “nottaken” branch before the instruction or set of instructions containingthe branch is executed by the microprocessor. It should be appreciatedby one skilled in the art that instructions will be structureddifferently in various embodiments of the invention where differentarchitectures and instruction sets are used by microprocessors such asprocessor(s) 104.

In step 210, index accelerator 320 is indexed to the row correspondingto the address of the first instruction received in the instructionstream and the information included in the current row of indexaccelerator 320 is read. In various embodiments, depending on the widthof the address space, various numbers of unique instruction addressesmay be present, and as a result different numbers of rows may berequired for index accelerator 320 in various embodiments of theinvention. Generally, only a subset of bits of the instruction addressfor a given instruction are used to identify the row number in indexaccelerator 320 which contains branch prediction data for the giveninstruction. For example, in an embodiment where 32-bit instructionaddresses are used (including bits 0 through 31), each instructionaddress is split into a left tag (L-tag) made up of the first 17 bits ofthe instruction address (bits 0 through 16), an index made up of thenext 10 bits of the instruction address (bits 17 through 26), and aright tag (R-tag) made up of the final 5 bits of the instruction address(bits 27 through 31). In this embodiment, because only the ten bits ofthe instruction address used as the index are used to determine the rowin index accelerator 320 in which the branch prediction data is storedfor that instruction, index accelerator 320 includes 1024 (210) rows.Further, in some embodiments index accelerator 320 is designed tocontain the same number of rows as BTB 310 and be indexed based on thesame 10 bits of the instruction address as BTB 310. In otherembodiments, BTB 310 and index accelerator 320 use different numbers ofbits to determine which row in the respective tables contain the branchprediction information for that instruction. In these embodiments, it ispossible for BTB 310 and index accelerator 320 to have different numbersof rows while still allowing for the invention to operate correctly.

In decision step 215, the data contained in the row of index accelerator320 corresponding to the current instruction is read to determine if abranch is expected for the current instruction. It should be appreciatedthat one row of index accelerator 320 can correspond to a large numberof instruction addresses in embodiments where aliasing is used, and thatin these embodiments multiple instruction addresses will correspond tothe same row in index accelerator 320. In one embodiments, the first bitof data stored in the current row of index accelerator 320 contains abinary indication of whether or not a taken prediction is present in thecorresponding row of BTB 310. In this embodiment, the determination ofwhether or not a taken prediction is present in the corresponding row ofBTB 310 is made using this single bit of data alone. In this embodiment,if the first bit of data is a zero indicating that there is not takenprediction present in the corresponding row of BTB 310 (decision step215, no branch), then processor(s) 104 determines if more instructionsare present in the instruction stream in decision step 225. If the firstbit of data is a one indicating that there is a taken prediction presentin the corresponding row of BTB 310 (decision step 215, yes branch),then processor(s) 104 identifies the target address of the first takenbranch indicated by the current row of index accelerator 320 in step220.

In step 220, processor(s) 104 identifies the target address of the firsttaken branch prediction indicated in the current row of indexaccelerator 320. In one embodiment, a single 17-bit binary number iscontained in each row of index accelerator 320. In this embodiment, thefirst bit of data present in a row “K” of index accelerator 320 is abinary indicator which indicates whether or not a valid prediction for ataken branch is expected to be present in any of the columns present inrow “K” of BTB 310. In this embodiment, because there are six columnspresent in BTB 310, six bits of additional data are used to indicatewhether the first taken prediction is present in each of the six columnspresent in the row “K” of BTB 310. In general, the “nth” digit of thesesix digits indicates that the “nth” column of row “K” of BTB 310 willcontain the first taken branch prediction. It should be appreciated thatonly one of the “n” digits can have a value of one at a given time. Inthis embodiment, the final 10 bits of data are used to store a portionof the predicted target address of the first taken branch predicted tobe stored in the row “K” of BTB 310. It should be appreciated that thenumber of bits of the target address stored in each row of indexaccelerator 320 varies in different embodiments of the invention. Insome embodiments, an additional structure such as a changing targetbuffer (CTB) may be used to predict the target address for the firsttaken prediction indicated by one or more rows of index accelerator 320.In these embodiments, the target address of the first taken predictionmay be omitted, and the indication of the column of BTB 310 is used tomore easily identify the target address of the first taken predictionusing the additional structure such as the CTB. In general, theindication of which column of row “K” of BTB 310 contains the firsttaken prediction is used in embodiments where additional structures suchas a CTB are used, or embodiments where the first taken branch is abranch of a certain type such as MCENTRY, MCEND, EX, or EXRL.

It should be appreciated that a prediction is drawn from BTB 310simultaneously while a prediction is drawn from index accelerator 320,and that the prediction drawn from index accelerator 320 is consideredvalid until confirmed or disputed by the prediction drawn from BTB 310,as described in greater detail with respect to FIG. 4. In the depictedembodiment, a prediction of a taken branch is drawn by examining thefirst bit of the 17-bit number included in the current row of indexaccelerator 320 to determine if a valid prediction is present, and if avalid prediction is present, then examining the last 10 bits of the17-bit number included in the current row of index accelerator 320 todetermine the target address of the predicted branch. It should beappreciated that the last 10 bits of the 17-bit number included in thecurrent row of index accelerator 320 represent a subset of the bits ofthe target address of the predicted branch. In various embodiments, thebits of data included in index accelerator 320 are the bits of data usedto re-index index accelerator 320 to the target address of theprediction. In embodiments where more or fewer bits of data are used tore-index index accelerator 320, the length of the number included in agiven row of index accelerator 320 will differ from the 17 bits of datadescribed in the current embodiment. Once the target address of thefirst taken branch prediction is identified, processor(s) 104 re-indexesindex accelerator 320 and BTB 310 to the rows corresponding to thetarget address for the first taken branch prediction. Once indexaccelerator 320 and BTB 310 are re-indexed, processor(s) 104 re-startsthe process of searching BTB 310 and index accelerator 320 for branchpredictions at the new target address in step 210.

In decision step 225, processor(s) 104 determines if there is moreaddress space to search. If the search logic decides that searchingshould stop (decision step 225, no more searching), then branchprediction search ends. A restart is a means by which processor 104begins a fresh new search stream in the branch prediction logic. Once arestart it occurs, processor 104 may keep searching sequentially forbranches. In other aspects, processor 104 may also acceleratere-indexing whenever index accelerator 320 finds an end of stream, soprocessor 104 redirects branch predictor 320 to start searching into anew stream. If a request for a restart is received with an instructionaddress following the previous instruction address (decision step 225,yes allowed to continue searching), then processor 104 continuessearching the next sequential rows of BTB 310 and index accelerator 320for predictions of the presence of branches in step 230. In the depictedembodiment, step 230 includes incrementing the index of the current rowsof BTB 310 and index accelerator 320 and starting a new search byreading the data included in the new current rows of BTB 310 and indexaccelerator 320. In general, the indexes of BTB 310 and indexaccelerator 320 are incremented because the next row in BTB 310 andindex accelerator 320 contains branch prediction information for thenext sequential set of instructions present in the instruction stream.

FIG. 3 is a block diagram of the components of branch target buffer(BTB) 310 and branch target buffer column predictor (CPRED) 320, inaccordance with an embodiment of the invention.

BTB 310 is a collection of tabulated data including “M” columns and “N”rows of data. In the depicted embodiment, the value of “M” is depictedas being 6, yielding an embodiment where BTB 310 contains a total of sixcolumns used to store the six most recent predictions for each rowpresent in BTB 310. In general, a given cell in BTB 310 is referred toas BTB(N, M), where “N” is the row number and “M” is the column number.It should be appreciated that the number of rows and columns included inBTB 310 varies in different embodiments of the invention and that thedepicted embodiment of BTB 310 which included 6 columns and 1024 rows isnot meant to be limiting. It should be appreciated by one skilled in theart that various methods for drawing predictions from the informationincluded in BTB 310 may be used in various embodiments of the invention,and that the invention is not limited to any specific method of drawingpredictions from the information included in BTB 310. Additionally, theinformation included in BTB 310 may be stored or encoded differently invarious embodiments of the invention, and the examples provided of howinformation is stored in BTB 310 is not meant to be limiting.

Index accelerator 320 is a one-dimensional array of data used inconjunction with BTB 310 by branch prediction logic to predict thecolumn in which the first taken prediction will be present in BTB 310for a given row. In some embodiments, index accelerator 320 contains thesame number of rows (“N”) as BTB 310, with a given row “K” in indexaccelerator 320 providing information related to the first takenprediction present in the corresponding row “K” of BTB 310. In otherembodiments, index accelerator 320 contains fewer rows than BTB 310, andin these embodiments aliasing is used to apply the column predictioncontained in row “K” of index accelerator 320 to multiple rows in BTB310. In general, decreasing the size of index accelerator 320 isdesirable in embodiments where reducing the amount of time required toaccess index accelerator 320 or limiting memory required by indexaccelerator 320 is important. Additionally, increasing the size of indexaccelerator 320 is desirable in embodiments where reducing the amount oftime required to access index accelerator 320 or limiting memoryrequired by index accelerator 320 is not important, and improving theaccuracy of each branch prediction is important. For example, in anembodiment where the address space has a dimension of three bits, BTB310 contains eight rows of data to ensure that each possible addresscorresponds to a unique row in BTB 310 which can be used to predict thepresence of branches in the instruction stream for that address. In thisexample, it is possible to use only two rows of data for indexaccelerator 320 and utilize the prediction contained in each row ofindex accelerator 320 for four rows of BTB 310. For example, if BTB 310includes rows numbered 1 through 8, then row 1 of index accelerator 320is used to provide a column prediction for rows 1 through 4 of BTB 310while row 2 of index accelerator 320 is used to provide a columnprediction for rows 5 through 8 of BTB 310.

In general, the data included in each row of index accelerator 320describes which column in BTB 310 contains the last first desired takenprediction for the corresponding row in BTB 310. In some embodiments,the address of the first taken branch target for a row “K” in BTB 310 isincluded in the entry for the corresponding row “K” in index accelerator320. The reason for including the address of the first taken branchtarget is to be able to re-index BTB 310 and index accelerator 320 tothe address of the first taken branch target without having to retrievethe address of the first taken branch target from BTB 310.

In various embodiments, BTB 310 and index accelerator 320 are accessedsimultaneously, and a prediction is drawn from both BTB 310 and indexaccelerator 320 independently. It should be appreciated by one skilledin the art that in these embodiments, many different methods for drawingpredictions from BTB 310 may be used. Because of the decreased number ofcycles required to draw a prediction from index accelerator 320, theprediction drawn from index accelerator 320 is used as a preliminaryprediction until confirmed by the prediction drawn from BTB 310. Inembodiments where the prediction drawn from BTB 310 is the same as theprediction drawn from index accelerator 320, branch prediction logicproceeds to continue retrieving additional predictions for the followinginstructions in the instruction stream. In embodiments where theprediction drawn from index accelerator 320 differs from the predictionlater drawn from BTB 310, the prediction drawn from BTB 310 is assumedto be more reliable and as a result BTB 310 and index accelerator 320are both re-indexed to the address of the first taken branch targetpredicted by BTB 310 and the column prediction data and address of thenew first taken branch target are updated for the corresponding row “K”in index accelerator 320.

FIG. 4 is a flowchart depicting the operational steps required toutilize BTB 310 and index accelerator 320 in conjunction with each otherto draw branch predictions and update the predictions stored in indexaccelerator 320 in the event that an incorrect prediction is present.

In step 405, BTB 310 is indexed to a row “K” corresponding to thecurrent instruction, and hit detection is performed on the row “K” todetermine which column (if any) contains a usable branch prediction forthat instruction. In general, it takes five clock cycles for a branchprediction to be reported using the information stored in BTB 310, andafter the first prediction is reported, additional prediction arereported once every four cycles. As a result of this, predictions drawnusing the information stored in BTB 310 alone can be issued every fourclock cycles. In this embodiment, due to predictions from indexaccelerator 320 being drawn faster (once every two clock cycles once thefirst prediction is reported), BTB 310 and index accelerator 320 areboth re-indexed once predictions are drawn from index accelerator 320every second clock cycle, and the predictions drawn from BTB 310 aloneare used to verify the predictions drawn from index accelerator 320 twoclock cycles earlier. The cycles required for drawing predictions fromthe information included in BTB 310 and index accelerator 320 aredescribed in greater detail with respect to FIGS. 5 and 6.

In step 410, index accelerator 320 is indexed to a row “K” correspondingto the current instruction and the prediction contained in the row “K”of index accelerator 320 is read. The prediction read from row “K” ofindex accelerator 320 is used to start a new search using the partialtarget address read from row “K” of index accelerator 320. In thedepicted embodiment, steps 405 and 410 begin simultaneously and occur inparallel when a new instruction is received by processor(s) 104. Ingeneral, it takes three clock cycles for a prediction to be reportedfrom the data included in index accelerator 320. In clock cycle 0, indexaccelerator 320 is indexed to the row “K” corresponding to the currentinstruction. In clock cycle 1, the information stored in the row “K” ofindex accelerator 320 is read by processor(s) 104, along withinformation describing which columns in BTB 310 is expected to containthe first taken branch. In clock cycle 2, the prediction of the firsttaken branch is reported and both BTB 310 and index accelerator 320 arere-indexed to the address of the first taken branch predicted by theinformation in row “K” of index accelerator 320. Both BTB 310 and indexaccelerator 320 are re-indexed at this time to ensure that the branchprediction search for the next target location occurs as soon aspossible. It should be appreciated that clock cycle 2 serves as clockcycle 0 for the following branch prediction search performed using theinformation stored in index accelerator 320.

In decision step 415, the prediction reported in step 410 is compared tothe prediction reported in step 405 to determine if index accelerator320 predicted the location and target of the first taken branch presentin BTB 310 correctly for the given branch. In one embodiment, the targetaddresses included in both branch predictions are compared to determineif there is any difference between the prediction reported in step 410and the prediction reported in step 405. In various embodiments, theprediction drawn from the data included in index accelerator 320includes only a subset of the bits of the target address of theprediction drawn from the information included in BTB 310. In theseembodiments, only the bits which are included in both predictions arecompared. If the predictions are equal (decision step 415, yes branch),then processor(s) 104 continues with the branch prediction searchinitiated in step 410 using the data received from index accelerator 320in step 425. If the predictions received are not equal (decision step415, no branch), then processor(s) 104 re-indexes index accelerator 320and BTB 310 to the first taken branch prediction reported in step 405,and starts the branch prediction search over from that point.

In step 420, BTB 310 and index accelerator 320 are re-indexed to theaddress of the first taken branch predicted in step 405. Additionally,the information stored in the row “K” of index accelerator 320 isupdated to reflect the prediction reported in step 405. In this process,the correct address of the branch target predicted in step 405 iswritten to row “K” of index accelerator 320 along with the column of BTB310 from which the prediction reported in step 405 was fetched.

In step 425, the search initiated in step 410 continues based on theprediction drawn from the information included in row “K” of indexaccelerator 320. It should be appreciated that the process of continuingthe search started in step 410 includes re-indexing index accelerator320 to the row corresponding to the target address of each new branchprediction as they are encountered. For example, in the depictedembodiment, a branch prediction included in row “K” of index accelerator320 includes a target address corresponding to row “L” of indexaccelerator 320. After re-indexing index accelerator 320 to row “L”, aprediction with a target address corresponding to row “M” is read. Ingeneral, the process of identifying successive predictions is referredto as continuing a search.

FIG. 5 is a timing diagram, generally designated 500, illustratingsuccessive branch prediction searches performed using BTB 310. Eachcolumn of timing diagram 500 present below row 550, such as columns 531,532, 533, 534, and 535 illustrates the current status of each branchprediction search currently being performed by processor 104 in a givenclock cycle, with the clock cycle number indicated by the cell presentwithin row 550 of that column. Each row of timing diagram 500 presentbelow row 550, such as rows 541, 542, 543, 544, and 545 illustrates thecurrent state of a branch prediction search performed by processor 104using BTB 310 in successive clock cycles. For the search represented bya given row of timing diagram 500, the row of BTB 310 currently beingsearched is indicated by the cell within column 520 of that row. Row 550indicates the current clock cycle of processor 104 performing thevarious branch prediction searches indicated by timing diagram 500.

Row 541 illustrates a branch prediction search with search address “X”which involves drawing a prediction using the information included inrow “X” of BTB 310. In the depicted embodiment, the prediction is drawnfrom the information included in row “X” of BTB 310 in the fifth cycleof the branch prediction search (B4) (row 541, col 531). In the depictedembodiment, the five cycles required for each branch prediction searchperformed using BTB 310 are B0, B1, B2, B3, and B4. In cycle B0, BTB 310is indexed to a starting search address of “X”. In some embodiments thestarting search address has additional properties associated with itsuch as an indication of whether or not the instructions received byprocessor 104 are in millicode, the address mode, a thread associatedwith the instructions received by processor 104, or other informationstored in BTB 310 in various embodiment of the invention. In general,cycle B1 is an access cycle for BTB 310 which serves as busy time whileinformation included in row “X” of BTB 310 is retrieved. In cycle B2,the entries in row “X” are returned from BTB 310 and hit detectionbegins. In various embodiments, hit detection includes ordering theentries in row “X” by instruction address space, filtering for duplicateentries, filtering for a millicode branch if the search is not for amillicode instruction or set of millicode instructions, or filtering forother criteria indicated by the entries present in row “X” of BTB 310.In some embodiments, hit detection additionally includes discarding anybranch with an address earlier than the starting search address andidentifying the first entry that is predicted to be taken. Additionally,any entry for a taken branch present after the first taken branch in theinstruction space may be discarded, and all of the remaining branchpredictions including the first taken branch prediction and a number ofnot taken branch predictions are reported. In cycle B3, hit detectioncontinues and concludes with an indication of whether or not any of theentries included in row “X” of BTB 310 contain a valid prediction of abranch which is expected to be encountered in the instruction stream. Incycle B4, the target address of the first taken prediction is reportedand a new branch prediction search is initiated with a search addressequivalent to the target address of the first taken prediction reported.

In the depicted embodiment, in clock cycle 1 a branch prediction searchwith a search address of “X” begins cycle BO (row 541, col 531). Inclock cycle 2, the branch prediction search with a search address of “X”advances to cycle B1 (row 541, col 532), while a new branch predictionsearch with a search address of “X+1” begins cycle B0 (row 542, col532). It should be appreciated that the index “X+1” represents the nextsequential portion of the address space present after “X”, and thatcorrespondingly row “X+1” represents the next row present in BTB 310present after row “X”. In clock cycle 3, the branch prediction searchwith a search address of “X” advances to cycle B2 (row 541, col 533),the branch prediction search with a search address of “X+1” advances tocycle B1 (row 542, col 533), and a new branch prediction search isinitiated with a search address of “X+2” (row 543, col 533). In clockcycle 4, the branch prediction search with a search address of “X”advances to cycle B3 (row 541, col 534), the branch prediction searchwith a search address of “X+1” advances to cycle B2 (row 542, col 534),the branch prediction search with a search address of “X+2” advances tocycle B1 (row 543, col 534), and a new branch prediction search isinitiated with a search address of “X+3” (row 544, col 534). In clockcycle 5, the branch prediction search with a search address of “X”advances to cycle B4 and issues a prediction of a first taken branchwith a target address of “Y” (row 541, col 535). As illustrated in thedepicted embodiment of the invention, a new branch prediction search isinitiated in clock cycle 5 with a search address of “Y” (row 545, col535). In some embodiments, the searches with search indices “X+1”,“X+2”, and “X+3” are cancelled upon the search with an index of “X”reporting a prediction for a taken branch. However, in the depictedembodiment, these searches continue to advance to the next cycles beforebeing cancelled following clock cycle 5.

In general, it should be appreciated that, using BTB 310 alone, branchprediction logic can identify a taken prediction up to once every fourclock cycles.

FIG. 6 is a timing diagram, generally designated 600, illustratingsuccessive branch prediction searches performed using BTB 310 and indexaccelerator 320. Similarly to FIG. 5, each column of timing diagram 600present below row 650, such as columns 631, 632, 633, 634, and 635illustrates the current status of each branch prediction searchcurrently being performed by processor 104 in a given clock cycle, withthe clock cycle number being indicated by the cell present within row650 of that column. Each row of timing diagram 600 present below row650, such as rows 641, 642, and 643 illustrates the current state of anindividual branch prediction search performed by processor 104 using BTB310 and index accelerator 320 in each clock cycle. For the searchrepresented by a given row of timing diagram 600, the row of BTB 310 andindex accelerator 320 currently being searched is indicated by the cellwithin column 620 of that row. Row 650 indicates the current clock cycleof processor 104 performing the various branch prediction searchesindicated by timing diagram 600.

Row 641 illustrates a branch prediction search with search address “X”which involves drawing a prediction using the information included inrow “X” of BTB 310 and row “X” of index accelerator 320. It should beappreciated that in some embodiments, different indexing structures areused for BTB 310 and index accelerator 320. In these embodiments, therow “X” of BTB 310 from which information is read will differ from therow of index accelerator 320 from which information is read. It shouldadditionally be appreciated that the embodiment where BTB 310 and indexaccelerator 320 use the same indexing structure serves as an example ofone embodiment and is not meant to be limiting. In the depictedembodiment, a prediction is drawn from the information included in row“X” of index accelerator 320 in the third cycle of the branch predictionsearch (cycle B2), and a prediction is drawn from the informationincluded in row “X” of BTB 310 in the fifth cycle of the branchprediction search (cycle B4). In the depicted embodiment, the fivecycles required for each branch prediction search performed usinginformation included in BTB 310 are the same five cycles B0 through B4as described in greater detail with respect to FIG. 5. In thisembodiment, the three cycles required to draw a prediction from theinformation included in row “X” of index accelerator 320 are B0, B1, andB2. In cycle B0, index accelerator 320 is indexed to a starting searchaddress of “X”. In some embodiments the starting search address hasadditional properties associated with it such as an indication ofwhether or not the instructions received by processor 104 are inmillicode, the address mode, a thread associated with the instructionsreceived by processor 104, or other information stored in BTB 310 orindex accelerator 320 in various embodiments of the invention. Ingeneral, cycle B1 is an access cycle for index accelerator 320 whichserves as busy time while information included in row “X” of indexaccelerator 320 is retrieved. In cycle B2, the target address of thefirst taken prediction is reported and a new branch prediction search isinitiated with a search address equivalent to the target address of thefirst taken prediction reported.

In the depicted embodiment, in clock cycle 1 a branch prediction searchwith a search address of “X” begins cycle B0 (row 641, col 631). Inclock cycle 2, the branch prediction search with a search address of “X”advances to cycle B1 (row 641, col 632), while a new branch predictionsearch with a search address of “X+1” begins cycle B0 (row 642, col632). It should be appreciated that the index “X+1” represents the nextsequential portion of the address space present after “X”, and thatcorrespondingly row “X+1” represents the next DWQ (or next incrementalbranch prediction search). In clock cycle 3, the branch predictionsearch with a search address of “X” advances to cycle B2 and returns aprediction of a first taken branch with a target address of “Y” (row641, col 633). As illustrated in the depicted embodiment of theinvention, a new branch prediction search is initiated in clock cycle 3with a search address of “Y” (row 643, col 633). In some embodiments,the search with search address “X+1” is cancelled upon the search withan index of “X” reporting a prediction for a taken branch. However, inthe depicted embodiment, these searches continue without beingcancelled. In clock cycle 4, the branch prediction search with a searchaddress of “X” advances to cycle B3 (row 641, col 634), the branchprediction search with a search address of “X+1” advances to cycle B2and returns a prediction of no taken branch (row 642, col 634), and thebranch prediction search with a search address of “Y” advances to cycleB1 (row 643, col 634). In some embodiments, a new branch predictionsearch with a search address of “Y+1” may begin in clock cycle 4,however no additional searches are depicted in FIG. 6. In clock cycle 5,the branch prediction search with a search address of “X” advances tocycle B4 and reports a prediction of a first taken branch with a targetaddress of “Y” (row 641, col 635) based on the information contained inBTB 310, confirming the prediction reported in clock cycle 3 using theinformation contained in index accelerator 320. Additionally in clockcycle 5, the branch prediction search with a search address of “X+1”advances to cycle B3 (row 642, col 635) and the branch prediction searchwith a search address of “Y” advances to cycle B2 and reports aprediction of no taken branch (row 643, col 635). In embodiments where abranch is predicted in clock cycle 5, a new branch prediction searchwith a search address equal to the target address of the branchprediction in clock cycle 5 may begin in clock cycle 5, however noadditional searches are depicted in FIG. 6.

In general, it should be appreciated that, using both BTB 310 and indexaccelerator 320, branch prediction logic can identify a taken branch upto once every two clock cycles. Additionally, it should be appreciatedthat the use of index accelerator 320 allows for predictions to bereported earlier and allows for the creation of a new search with asearch address equivalent to the target address of a taken branchprediction in cycle B2 as opposed to cycle B4.

According to some embodiments discussed thus far, the SPRED's outputwill tell the branch prediction logic where it thinks the exit point, ortaken branch that ends the stream is located. For instance, at the startof stream 0, the start IA of 0x00 would be used to index into the streambased index accelerator 320, and SPRED's output would indicate the exitpoint is X DWQs from the start of stream 0. The SPRED output would beused to accelerate indexing into stream 1 once X DQWs were searched instream 0, where it would then be indexed with start IA x50, and wouldproduce an output of Y DQWs, indicating where the exit point of stream 1resides, etc. With this scheme, the SPRED would only need to be readonce per stream, with the starting search address of the stream (forexample) and in the SPRED entry would be the information containing theDQW offset that the exit point is at.

As described previously, the BTB is generally indexed using aninstruction address, and is incremented by a certain amount to continuesearching sequentially for branching within a region of code. Each timethe processor instruction stream is restarted, such as for a branchwrong, searching starts and what is known as a new stream. Therefore,each predicted taken branch starts a new stream.

In some instances, a stream starting from a certain search address couldhave different behaviors and consequentially different taken branchesthat end the stream. FIG. 7 is a diagram illustrating a stream basedcolumn predictor (SPRED) indexed at the start of each stream. Asdepicted in FIG. 8, the same stream 0 now predicts the branch atinstruction address (IA) 0x00+X DQW to be not taken, and instead adifferent branch further downstream within stream 0 is predicted takento a different address IA 0x80. As shown in FIG. 7, processor 104 gets arestart and starts execution at instruction address (IA) 0x00. This isthe beginning of stream 0. At an instruction address (IA) of 0x00+XDQWs, a taken branch ends stream 0 and starts stream 1 at the targetaddress of the branch ending stream 0, IA x50. Stream 1 ends at an IA of0x50+Y DQWs where a taken branch's target IA is 0x6A, where subsequentstream 2 starts, and so on.

In the example of FIG. 7, a stream based column predictor (SPRED) wouldbe indexed at the start of each stream. Its output will tell the branchprediction logic where it thinks the exit point, or taken branch thatends the stream, is located. For instance, at the start of stream 0, thestart IA of 0x00 would be used to index into the stream based SPRED, andthe SPRED's output would indicate the exit point is X DWQs from thestart of stream 0. The SPRED output would be used to accelerate indexinginto stream 1 once X DQWs were searched in stream 0, where it would thenbe indexed with start IA x50, and would produce an output of Y DWQs,indicating where the exit point of stream 1 resides, etc. One potentialoutcome, however, is that a stream could have more than one taken branchwhich would end the stream. FIG. 8 is a diagram illustrating the streambased column predictor (SPRED) of FIG. 7 having a branch not taken.

Referring now to FIG. 8, according to some embodiments, the same stream0 may now predict the branch at instruction address (IA) 0x00+X DQW tobe not taken, and instead the processor may predict a different branchfurther downstream within stream 0 as a taken branch to a different IA,0x80. In some aspects, a stream based SPRED would do the following: atthe start of stream 0, it would be indexed with IA 0x00 and predict theend of the stream is X DQWs from the start of stream 0. Once X DQWs aresearched, the SPRED would incorrectly redirect the BPL to IA x50. Logicthat validates the SPRED prediction would realize that the exit pointreally was not X DQWs from the start of stream 0, but rather X′ DQWs.Each time the column predictor is incorrect, the processor updates witha location of the exit point for the end of the stream.

In the example depicted in FIG. 8, the SPRED entry at index location0x00 would change from X to X′. In this example, if the programeventually starts back at the stream at IA 0x00 again, the SPRED wouldpredict the exit point is X′ DQWs from the start of the stream. If thebehavior of the code reverted to the first case, where the exit point isX DQWs from the start of the stream, the SPRED could incorrectly predictthe exit point for stream 0 is X′ DQWs, when it was really X DQWs. Therecould be one branch that ends the stream most of the time, and every sooften a different branch ends the same stream, as in the above example.

FIG. 9 is a flowchart depicting a computer-implemented method 900 forpredicting a branch in an instruction stream having more than one exitin a pipelined high frequency microprocessor, according to oneembodiment. According to some embodiments, each column predictor entrywould contain the following information to help identify the most commontaken branch from a stream, including: a location of the end of thestream, a first exit point “A” (such as the number of double quadwords(DQW) in from the start of the stream the taken branch is expected to befound and column location), a location of another end of a stream (exitpoint “B”), a counter for exit point A, and a counter for the secondexit point B.

According to some embodiments, each SPRED entry may contain two DQWvalues for the locations of exit points A and B. The processor may usethe first exit point (A) as the primary or default prediction for thetaken branch (referred to also as an exit point or a branch exit point)for the stream. Each of the first and second exit points A and B mayalso include a counter that is incremented every time that particularexit point is or would have been correct. Although this example depictstwo taken branches, according to other embodiments, each stream maycontain information on more than two stream exit points. Processor 104may observe any number of taken branches.

Referring now to FIG. 9, after an initial start step 902, after a newcolumn predictor entry, processor 104 may index the BTB and perform hitdetection. Accordingly, processor 104 may receive a first instructionwithin a first instruction stream, where the first instruction includesDQW values for the locations of exit points A (a first instructionaddress) and B (a second instruction address). According to someembodiments, the first exit point A may be a predetermined default exitpoint. Processor 104 may select a current row of the BTB and acorresponding current row of a one-dimensional array, based at least inpart, on a first count value indicative of a taken branch frequency. Thetaken branch frequency count value may be indicative of a predictionaccuracy. In some aspects, the higher the frequency counter, the better(more accurate) the prediction it represents, because each countindicates one instance of a correct prediction observed by processor104.

Accordingly, processor 104 may place the exit DQW of the stream into afirst exit point (position A, which has the first instruction address)and the first counter value for the first exit point prediction, whichis initially set as the default exit point, is set to 0. Processor 104may receive a first instruction within a first instruction stream thatincludes a first instruction address. Processor 104 may perform a hitdetection by searching an index accelerator predictor one time for thestream.

As shown in block 906, processor 104 may determine whether the defaulttaken branch (which is a first exit address ending the instructionstream) is correct. Each taken branch observed by processor 104 mayinclude its own frequency count indicative of when that particularbranch matches the default predicted branch (e.g., branch exit point A).Whenever the default SPRED exit accelerator predictor is correct, asshown in block 910, processor 104 may increment the frequency count ofthe default taken branch counter that taken makes a correct columnpredictor prediction, its counter is incremented (e.g., saved countervalue=saved value+1). Processor returns to index the BTB 310 and performanother hit detection, as shown in block 904.

As shown in block 918, processor 104 may update the second exit point(taken branch) of the branch prediction stream, and determine at block912 whether the prediction for the second taken branch is correct.

As shown in block 906, when processor 104 encounters another takenbranch for the same stream (the column predictor using exit point A) waswrong, processor 104 may determine whether the second taken branch wascorrect, as shown in block 912. Accordingly, updating may includereplacing a prediction for a least frequently observed taken branch withthe prediction for a more recently used taken branch ending the branchstream.

As shown in block 914, processor 104 may update the second taken branchprediction when the second taken branch (the observed taken branch) iscorrect. Updating may include increasing a frequency count indicative ofwhen the observed taken branch matches one of the plurality of takenbranches. Accordingly, processor 104 may place the new DQW exit pointinto exit position B (the second taken branch), and set the second takenbranch count value indicative of the second prediction accuracy to 0.Processor 104 may replace the second count value with zero if the secondtaken branch prediction is not correct, as shown in block 918.Accordingly, if the column predictor continues to make bad predictionsusing exit point A, but the DQW exit point in B would have been correct,processor 104 may be configured to increment exit point B's counter. Asshown in block 916, processor 104 may determine whether the second countis greater than the default count. Processor 104 may set either thefirst exit point of the branch prediction stream or the second exitpoint of the branch prediction stream as a default target address basedthe prediction accuracy as determined by the counter values.

According to some embodiments, as shown in block 920, whenever exitpoint B's counter exceeds exit point A's counter, processor 104 may swapthem such that B is now in A's position and future column predictorpredictions would be made with the exit position with the higher countvalue. The swap indicates that exit point A's count value should alwaysbe greater than exit point B's. When exit point A's count valuesaturates at all ones, processor 104 may divide the first and secondexit point's counters by two. Any new DQW exit points may replace thevalue in exit point position B, again zeroing out exit point B'scounter.

The process begins again at block 904 by indexing the BTB and performinga hit detection.

Employing this approach, index accelerator 320 may continue to maintainknowledge of the most frequent exit point from the stream. If indexaccelerator 320 encounters another exit point that was more frequentthan the one currently being used for SPRED predictions, then it canswitch to using the more frequently used exit point. index accelerator320 is thus able to track multiple exits from the stream, keeping trackof the most common exit point and predict using the most common exitpoint.

Some embodiments provide an efficient way to improve branch predictionthroughput. Some aspects may accelerate re-indexing of an asynchronouslookahead branch predictor for taken predictions. Embodiments may alsoprovide power prediction information to power down branch predictioncomponents that are not needed for a particular stream of instructions.

In some aspects, each SPRED entry may indicate where a stream ends,where the next stream begins, and the component branch predictors thatare needed in the next stream. Upon accelerating the index into the nextstream, the power prediction information may be used to only power upthe structures expected to be needed. According to some embodiments, itmay be advantageous to accelerate re-indexing of an asynchronouslookahead branch predictor for taken predictions, and provide powerprediction information to power down branch prediction components thatare not needed for a particular stream of instructions. Accordingly,such an arrangement may be more energy efficient and provide a largercomputational capacity. Like index accelerator 320, index accelerator320 can be written at prediction time. Processor 104 may install anentry upon making a qualifying taken prediction that was not acceleratedbecause it was not found in index accelerator 320.

Qualifying can depend on the type of branch instruction (informationfrom the BTB 310) and the source predictors of the target address. Forinstance branches with CTB-provided target addresses may not qualify forbeing accelerated by index accelerator 320. Additionally if indexaccelerator 320 is used and the branch prediction search process did notfind a qualifying taken branch in the search offset and column expected,then that SPRED entry is written to invalidate it. If index accelerator320 is used and a different qualifying taken branch is found, then theinstall rule causes the incorrect SPRED entry to be overwritten with thenewly installed one.

To write power prediction information into index accelerator 320, uponusing or installing a SPRED entry corresponding to start of stream X,processor 104 may remember its power prediction information. Uponinstalling a new entry power prediction is written based onimplementation dependent install policy: processor 104 could write toinitially power up all structures, power down all structures, orselectively power up some of the structures. For all searches in streamX+1, logic monitors which prediction structures are needed for branchesfound within the stream. This includes all predicted not-taken branchesand the predicted taken branch ending the stream. Upon predicting thetaken branch ending stream X+1, if the monitored needed structureinformation differs from the power prediction from SPRED entry forstream X, processor 104 may write the updated information into the entryindexed with the starting search address of stream X.

Power prediction information can include, but is not limited to thecolumns in BTB 310 that are needed, the columns in the branch historytable (BHT) that are needed, and whether pattern history table (PHT),changing target buffer (CTB), or perceptron predictors are needed.

According to some embodiments, processor 104 may access indexaccelerator 320 “inline” along with the search process as describedabove. Processor 104 may also access index accelerator 320 in alookahead manner. In that case the SPRED would re-index itselfimmediately upon finding a hit. The results would be queued and appliedto accelerate the re-index of the BPL search process when the oldestqueued SPRED result matches the current search stream and search numberoffset within that stream.

Some disclosed embodiments described herein extend the idea of thebranch target buffer column predictor (CPRED) and make it more efficientby storing stream based index accelerator prediction (SPRED) entries foreach stream of instructions, where a stream is a sequence ofinstructions ending with a taken branch rather than with every searchaddress. There are often multiple sequential search addresses within astream. Furthermore this stream-based organization allows for a largecapacity power predictor. Each SPRED entry indicates where a streamends, where the next stream begins, and the component branch predictorsthat are needed in the next stream. According to some embodiments, uponaccelerating the index into the next stream, processor 104 uses powerprediction information to only power up the structures expected to beneeded.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method for predicting aninstruction that ends an instruction stream in a pipelined highfrequency microprocessor, the method comprising: receiving, by aprocessor, a first instruction within a first instruction stream, thefirst instruction comprising a first instruction address; searching, bythe processor, a stream-based index accelerator predictor based on thefirst instruction address, wherein the stream-based index acceleratorpredictor comprises a one dimensional array comprising a plurality ofrows, wherein each row of the plurality of rows comprises dataindicative of a prediction of which column of a plurality of columns ofa corresponding row of a metadata prediction engine will include a firsttaken prediction; searching, by the processor, the metadata predictionengine based on the first instruction address, wherein the searching ofthe metadata prediction engine and the searching of the stream-basedindex accelerator is initiated at approximately the same time;determining, by the processor based on the searching of the stream-basedindex accelerator prior to an execution of the first instruction, afirst prediction for an ending instruction of the first instructionstream that ends the first instruction stream and a starting address ofa second instruction stream, the ending instruction comprising a secondinstruction address, wherein the first prediction is determined prior toan end of the searching of the metadata prediction engine; using thefirst prediction as a preliminary prediction; determining, by theprocessor based on the searching of the metadata prediction engine, asecond prediction for an ending instruction of the first instructionstream that ends the first instruction stream and a starting address ofa second instruction stream; influencing, by the processor, the metadataprediction engine based on the first prediction; and responsive todetermining that the first prediction does not match the secondprediction, updating, by the processor, the stream-based indexaccelerator predictor with information indicative of the secondprediction by updating the prediction of which column of a plurality ofcolumns of a corresponding row of a metadata prediction engine willinclude the first taken prediction.
 2. The computer-implemented methodof claim 1, wherein the metadata prediction engine comprises a branchtarget buffer.
 3. The computer-implemented method of claim 1, whereinthe metadata prediction engine comprises an auxiliary direction table ortarget prediction table.
 4. The computer-implemented method of claim 1,wherein influencing comprises accelerating a re-index of the metadataprediction structures.
 5. The computer-implemented method of claim 1,wherein influencing comprises making a power structure determinationthat determines which of the metadata prediction structures should bepowered up or powered down; and powering up or powering down one or moreof the metadata prediction structures based on the power structuredetermination.
 6. The computer-implemented method of claim 1, whereinthe prediction comprises information indicative of an end of the firstinstruction stream and a start of a next instruction stream.
 7. Thecomputer-implemented method of claim 1, wherein the prediction comprisesone or more of a location information—instruction address and a locationwithin the metadata prediction structures of the predicted taken branchending the stream.
 8. The computer-implemented method of claim 1,wherein the prediction comprises a target address of the taken branchpredicted to end the stream.
 9. A system for predicting an instructionthat ends an instruction stream in a pipelined high frequencymicroprocessor, the system comprising a processor configured to: receivea first instruction within a first instruction stream, the firstinstruction comprising a first instruction address; search astream-based index accelerator predictor based on the first instructionaddress, wherein the stream-based index accelerator predictor comprisesa one dimensional array comprising a plurality of rows, wherein each rowof the plurality of rows comprises data indicative of a prediction ofwhich column of a plurality of columns of a corresponding row of ametadata prediction engine will include a first taken prediction;search, by the processor, the metadata prediction engine based on thefirst instruction address, wherein the searching of the metadataprediction engine and the searching of the stream-based indexaccelerator is initiated at approximately the same time; determine,based on the searching of the stream-based index accelerator prior to anexecution of the first instruction, a first prediction comprising aprediction for an ending instruction of the first instruction stream anda starting address of a second instruction stream, the endinginstruction comprising a second instruction address, wherein the firstprediction is determined prior to an end of the search of the metadataprediction engine; use the first prediction as a preliminary prediction;determine, by the processor based on the searching of the metadataprediction engine, a second prediction for an ending instruction of thefirst instruction stream that ends the first instruction stream and astarting address of a second instruction stream; influence the metadataprediction engine based on the first prediction; and responsive todetermining that the first prediction does not match the secondprediction, update the stream-based index accelerator predictor withinformation indicative of the second prediction by updating theprediction of which column of a plurality of columns of a correspondingrow of a metadata prediction engine will include the first takenprediction.
 10. The system of claim 9, wherein the mainline branchprediction engine comprises a branch target buffer.
 11. The system ofclaim 9, wherein the mainline branch prediction engine comprises anauxiliary direction table or target prediction table.
 12. The system ofclaim 9, wherein influencing comprises accelerating a re-index of themainline branch prediction structures.
 13. The system of claim 9,wherein influencing comprises making a power structure determinationthat determines which of the mainline prediction structures should bepowered up or powered down; and powering up or powering down one or moreof the mainline predictions structures based on the power structuredetermination.
 14. The system of claim 9, wherein the predictioncomprises information indicative of an end of the first instructionstream and a start of a next instruction stream.
 15. The system of claim9, wherein the prediction comprises one or more of a locationinformation—instruction address and a location within the metadataprediction structures of the predicted taken branch ending the stream.16. The system of claim 9, wherein the prediction comprises a targetaddress of the taken branch predicted to end the stream.
 17. A computerprogram product for predicting an instruction that ends an instructionstream in a pipelined high frequency microprocessor, the computerprogram product comprising a computer readable storage medium havingprogram instructions embodied therewith, wherein the computer readablestorage medium is not a transitory signal per se, the programinstructions executable by a processor to cause the processor to performa method comprising: receiving, by the processor, a first instructionwithin a first instruction stream, the first instruction comprising afirst instruction address; searching, by the processor, a stream-basedindex accelerator predictor based on the first instruction address,wherein the stream-based index accelerator predictor comprises a onedimensional array comprising a plurality of rows, wherein each row ofthe plurality of rows comprises data indicative of a prediction of whichcolumn of a plurality of columns of a corresponding row of a metadataprediction engine will include a first taken prediction; searching, bythe processor, the metadata prediction engine based on the firstinstruction address, wherein the searching of the metadata predictionengine and the searching of the stream-based index accelerator isinitiated at approximately the same time determining, by the processorbased on the searching of the stream-based index accelerator prior to anexecution of the first instruction, a first prediction for an endinginstruction of the first instruction stream and a starting address of asecond instruction stream, the ending instruction comprising a secondinstruction address, wherein the first prediction is determined prior toan end of the searching of the metadata prediction engine; using thefirst prediction as a preliminary prediction; determining, by theprocessor based on the searching of the metadata prediction engine, asecond prediction for an ending instruction of the first instructionstream that ends the first instruction stream and a starting address ofa second instruction stream; influencing, by the processor, the metadataprediction engine based on the first prediction; and responsive todetermining that the first prediction does not match the secondprediction, updating, by the processor, the stream-based indexaccelerator predictor with information indicative of the secondprediction by updating the prediction of which column of a plurality ofcolumns of a corresponding row of a metadata prediction engine willinclude the first taken prediction.
 18. The computer program product ofclaim 17, wherein the metadata prediction engine comprises an auxiliarydirection table or target prediction table.
 19. The computer programproduct of claim 18, wherein the prediction comprises informationindicative of an end of the first instruction stream and a start of anext instruction stream.
 20. The computer program product of claim 17,wherein influencing comprises accelerating a re-index of the metadataprediction structures.